Rapid evaluation of strong ground‐shaking maps after moderate‐to‐large earthquakes is crucial to recognizing those areas where the largest damage and losses are expected. These maps play a fundamental role for emergency management. This is particularly important for areas having high seismic risk potential and covered by dense seismic networks. In near‐real‐time applications, ground‐shaking maps are produced by integrating recorded data and estimates obtained by using ground‐motion predictive equations, which assume point‐source models. However, particularly for large earthquakes, improvements in the predictions of the peak ground motion can be obtained when fault extension and orientation are available. In fact, detailed source information allows one to use a more robust source‐to‐site distance metric compared with hypocentral distance.
In this paper, a technique for estimating both fault extent (in terms of its surface projection) and dominant rupture direction is presented. This technique can be used in near‐real‐time ground‐motion map calculation codes with the aim of improving ground‐motion estimates with respect to a point‐source model. The model parameters are estimated by maximizing a probability density function based on the residuals between observed and predicted peak‐ground‐motion quantities, the latter obtained by using predictive equations. The model space to be investigated is defined through a Bayesian approach, and it is explored by a grid‐searching technique. The effectiveness of the proposed technique is demonstrated by offline numerical tests using data from three earthquakes occurring in different seismotectonic environments. The selected earthquakes are the 17 August 1999 Mw 7.5 Kocaeli (Turkey) earthquake, the 6 April 2009 Mw 6.3 L’Aquila (Italy) earthquake, and the 17 January 1994 Mw 6.7 Northridge (California) earthquake. The obtained results show that the proposed technique allows for fast and first order estimates of the fault extent and dominant rupture direction, which could be used to improve ground‐shaking map calculations.